Hospitals and their information systems are often in need of upgrades to keep up with the pace of our aging population. Data management can go a long way in easing this strain, but a number of situations unique to hospital systems can limit data management effectiveness.
We have either read about or been directly involved in system implementations that have not been delivered on time or performed exactly as promised. The impact can range from lost revenue to lost careers for the people who built the system. For hospital systems, though, the stakes are much higher. Downtime of systems can have a direct life-or-death impact on patients. Because many business owners group all applications, transactional and analytic, into "the system," there is a unique challenge in deploying data management solutions in this environment.
As one director of IT at a hospital stated, "Our business users see it all as one big system and do not want to take on the risk of a system failure. Their view is that even if the patient-admitting system is brought down, it will slow the input of patients and can have negative impacts on patient health. So they continue on with systems that are built in older, less flexible environments with very limited reporting and practically no analytics capability. From a system-integration perspective, we know that our reporting and analytic systems are really downstream, but getting our business counterparts to understand that is quite a challenge. Adding to our problem is the intense concern over patient privacy protection from HIPAA (Health Insurance Portability and Accountability Act) and how we need to keep our systems under compliance."
Follow the Process
To address concerns about the criticality of uptime for patient systems, the data management professional must be able to talk about how the systems can improve the business processes.
One of the best ways to understand the data needs is actually through the process. Most hospital organizations have some form of process documentation and/or standard operating procedures. These process flows should be mapped to the systems that support them. In many cases, this is an augmentation of the existing process maps and can be accomplished in a fairly short amount of time without much burden on key business users.
Armed with a system-centric process map, data management professionals can now dig into the data waypoints. Data waypoints are natural places along the process where data is either critical in making a decision on the process flow or data is produced as a byproduct of the decision. For example, in the patient admission process, there is a point where insurance coverage information is gathered. This is a natural data waypoint in that the insurance information provided by the patient determines the next course of action; but more important to the data management professional are the data byproducts produced at this point in the process.
Moving along the process flow, you will find intrasystem data waypoints, such as the admission decision point and intersystem data waypoints where the patient moves from the inbound admission process to the admitting active process.
Analyzing these waypoints will take some effort, and a decision should be made to concentrate on those that are expected to provide the highest level of value and present the lowest level of resistance to change.
Now, when discussing reporting and analytic systems with business users, the data management professional is armed with an understanding of the process, systems and data waypoints.
By concentrating on the data byproducts at certain waypoints, the data management professional can show how providing reporting and analytics against this data will minimize or eliminate the fear of system failure so prevalent in hospital system owners. In most cases, a traditional lift-and-shift approach of taking the data out into a reporting and analytic database is preferred.
Collecting these byproducts and putting them into a separate reporting or OLAP environment may not be the most technically savvy solution, but it goes a long way in easing the fears of the business users.
Leverage Your Subject Matter Expert
When architecting the approach, the data management professional must enlist a compliance subject matter expert, particularly in the area of HIPAA. As data moves into the reporting environment, a compliance risk is created. The order and magnitude of this risk is best understood by a person who lives and breathes compliance every day, such as a compliance department and/or a vendor with whom you have a relationship. This will ease the HIPAA risk concern of the business users and ensure a compliant solution.
Hospital systems provide unique situations and challenges for data management professionals in two areas: system uptime and compliance. Analyzing data waypoints is one great way to ease the system uptime concerns of the business users; enlisting subject matter expertise for compliance is the other. Armed with these two methods, data management professionals can make a real difference in the business and patient care.
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